标题： 双通道最小曲面优化方法：用于换热器设计的隐式双重通道最小曲面优化 显示英文标题

标题： DualMS: Implicit Dual-Channel Minimal Surface Optimization for Heat Exchanger Design

摘要： 换热器是在从能源系统到化学加工的广泛应用中的关键部件，在这些应用中高效的热管理至关重要。 换热器的设计目标包括在最小化压力损失的同时最大化传热速率，这需要较大的传热界面面积和光滑的内部结构。 先进的设计，如三重周期极小曲面（TPMS），已被证明在优化传热效率方面是有效的。 然而，TPMS设计受到预定义数学方程的限制，限制了它们适应自由形状边界的能力。 此外，TPMS结构本身并不控制流动方向，这可能导致流动停滞和不必要的压力损失。 本文提出了一种名为DualMS的新计算框架，专门用于优化自由形式形状下的双通道极小曲面换热器设计。 据我们所知，这是首次直接针对双流体换热器优化极小曲面，而不是依赖于TPMS。 我们的方法将最大传热问题表述为图上的约束连接最大割问题，流约束指导优化过程。 为了应对不必要的压力损失，我们将极小曲面建模为两种流体之间的分类边界，并引入了一个额外的区域最小化正则化项。 我们采用一种神经网络将空间点映射到二元流类型上，从而能够对其流动骨架进行分类并自动确定表面边界。 与TPMS相比，DualMS在表面拓扑方面表现出更大的灵活性，并且在保持相同材料成本的情况下实现了更好的热性能，同时具有更低的压力损失和相似的传热率。 显示英文摘要

摘要： Heat exchangers are critical components in a wide range of engineering applications, from energy systems to chemical processing, where efficient thermal management is essential. The design objectives for heat exchangers include maximizing the heat exchange rate while minimizing the pressure drop, requiring both a large interface area and a smooth internal structure. State-of-the-art designs, such as triply periodic minimal surfaces (TPMS), have proven effective in optimizing heat exchange efficiency. However, TPMS designs are constrained by predefined mathematical equations, limiting their adaptability to freeform boundary shapes. Additionally, TPMS structures do not inherently control flow directions, which can lead to flow stagnation and undesirable pressure drops. This paper presents DualMS, a novel computational framework for optimizing dual-channel minimal surfaces specifically for heat exchanger designs in freeform shapes. To the best of our knowledge, this is the first attempt to directly optimize minimal surfaces for two-fluid heat exchangers, rather than relying on TPMS. Our approach formulates the heat exchange maximization problem as a constrained connected maximum cut problem on a graph, with flow constraints guiding the optimization process. To address undesirable pressure drops, we model the minimal surface as a classification boundary separating the two fluids, incorporating an additional regularization term for area minimization. We employ a neural network that maps spatial points to binary flow types, enabling it to classify flow skeletons and automatically determine the surface boundary. DualMS demonstrates greater flexibility in surface topology compared to TPMS and achieves superior thermal performance, with lower pressure drops while maintaining a similar heat exchange rate under the same material cost.